International Science Index
Accuracy of Autonomy Navigation of Unmanned Aircraft Systems through Imagery
The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.
Application of Rapidly Exploring Random Tree Star-Smart and G2 Quintic Pythagorean Hodograph Curves to the UAV Path Planning Problem
This work approaches the automatic planning of paths
for Unmanned Aerial Vehicles (UAVs) through the application of the
Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm.
RRT*-Smart is a sampling process of positions of a navigation
environment through a tree-type graph. The algorithm consists of
randomly expanding a tree from an initial position (root node) until
one of its branches reaches the final position of the path to be
planned. The algorithm ensures the planning of the shortest path,
considering the number of iterations tending to infinity. When a
new node is inserted into the tree, each neighbor node of the
new node is connected to it, if and only if the extension of the
path between the root node and that neighbor node, with this new
connection, is less than the current extension of the path between
those two nodes. RRT*-smart uses an intelligent sampling strategy
to plan less extensive routes by spending a smaller number of
iterations. This strategy is based on the creation of samples/nodes
near to the convex vertices of the navigation environment obstacles.
The planned paths are smoothed through the application of the
method called quintic pythagorean hodograph curves. The smoothing
process converts a route into a dynamically-viable one based on the
kinematic constraints of the vehicle. This smoothing method models
the hodograph components of a curve with polynomials that obey
the Pythagorean Theorem. Its advantage is that the obtained structure
allows computation of the curve length in an exact way, without the
need for quadratural techniques for the resolution of integrals.
Automatic Landmark Selection Based on Feature Clustering for Visual Autonomous Unmanned Aerial Vehicle Navigation
The selection of specific landmarks for an Unmanned
Aerial Vehicles’ Visual Navigation systems based on Automatic
Landmark Recognition has significant influence on the precision of
the system’s estimated position. At the same time, manual selection
of the landmarks does not guarantee a high recognition rate, which
would also result on a poor precision. This work aims to develop an
automatic landmark selection that will take the image of the flight
area and identify the best landmarks to be recognized by the Visual
Navigation Landmark Recognition System. The criterion to select
a landmark is based on features detected by ORB or AKAZE and
edges information on each possible landmark. Results have shown
that disposition of possible landmarks is quite different from the
Development of an Indoor Drone Designed for the Needs of the Creative Industries
With this contribution, we want to show how the AiRT system could change the future way of working of a part of the creative industry and what new economic opportunities could arise for them. Remotely Piloted Aircraft Systems (RPAS), also more commonly known as drones, are now essential tools used by many different companies for their creative outdoor work. However, using this very flexible applicable tool indoor is almost impossible, since safe navigation cannot be guaranteed by the operator due to the lack of a reliable and affordable indoor positioning system which ensures a stable flight, among other issues. Here we present our first results of a European project, which consists of developing an indoor drone for professional footage especially designed for the creative industries. One of the main achievements of this project is the successful implication of the end-users in the overall design process from the very beginning. To ensure safe flight in confined spaces, our drone incorporates a positioning system based on ultra-wide band technology, an RGB-D (depth) camera for 3D environment reconstruction and the possibility to fully pre-program automatic flights. Since we also want to offer this tool for inexperienced pilots, we have always focused on user-friendly handling of the whole system throughout the entire process.
Dynamic Reroute Modeling for Emergency Evacuation: Case Study of Brunswick City, Germany
The human behaviors during evacuations are quite complex. One of the critical behaviors which affect the efficiency of evacuation is route choice. Therefore, the respective simulation modeling work needs to function properly. In this paper, Simulation of Urban Mobility’s (SUMO) current dynamic route modeling during evacuation, i.e. the rerouting functions, is examined with a real case study. The result consistency of the simulation and the reality is checked as well. Four influence factors (1) time to get information, (2) probability to cancel a trip, (3) probability to use navigation equipment, and (4) rerouting and information updating period are considered to analyze possible traffic impacts during the evacuation and to examine the rerouting functions in SUMO. Furthermore, some behavioral characters of the case study are analyzed with use of the corresponding detector data and applied in the simulation. The experiment results show that the dynamic route modeling in SUMO can deal with the proposed scenarios properly. Some issues and function needs related to route choice are discussed and further improvements are suggested.
Relative Navigation with Laser-Based Intermittent Measurement for Formation Flying Satellites
This study presents a precise relative navigational method for satellites flying in formation using laser-based intermittent measurement data. The measurement data for the relative navigation between two satellites consist of a relative distance measured by a laser instrument and relative attitude angles measured by attitude determination. The relative navigation solutions are estimated by both the Extended Kalman filter (EKF) and unscented Kalman filter (UKF). The solutions estimated by the EKF may become inaccurate or even diverge as measurement outage time gets longer because the EKF utilizes a linearization approach. However, this study shows that the UKF with the appropriate scaling parameters provides a stable and accurate relative navigation solutions despite the long measurement outage time and large initial error as compared to the relative navigation solutions of the EKF. Various navigation results have been analyzed by adjusting the scaling parameters of the UKF.
Tidal Current Behaviors and Remarkable Bathymetric Change in the South-Western Part of Khor Abdullah, Kuwait
A study of the tidal current behavior and bathymetric changes was undertaken in order to establish an information base for future coastal management. The average velocity for tidal current was 0.46 m/s and the maximum velocity was 1.08 m/s during ebb tide. During spring tides, maximum velocities range from 0.90 m/s to 1.08 m/s, whereas maximum velocities vary from 0.40 m/s to 0.60 m/s during neap tides. Despite greater current velocities during flood tide, the bathymetric features enhance the dominance of the ebb tide. This can be related to the abundance of fine sediments from the ebb current approaching the study area, and the relatively coarser sediment from the approaching flood current. Significant bathymetric changes for the period from 1985 to 1998 were found with dominance of erosion process. Approximately 96.5% of depth changes occurred within the depth change classes of -5 m to 5 m. The high erosion processes within the study area will subsequently result in high accretion processes, particularly in the north, the location of the proposed Boubyan Port and its navigation channel.
A Real-Time Simulation Environment for Avionics Software Development and Qualification
The development of guidance, navigation and control algorithms and avionic procedures requires the disposability of suitable analysis and verification tools, such as simulation environments, which support the design process and allow detecting potential problems prior to the flight test, in order to make new technologies available at reduced cost, time and risk. This paper presents a simulation environment for avionic software development and qualification, especially aimed at equipment for general aviation aircrafts and unmanned aerial systems. The simulation environment includes models for short and medium-range radio-navigation aids, flight assistance systems, and ground control stations. All the software modules are able to simulate the modeled systems both in fast-time and real-time tests, and were implemented following component oriented modeling techniques and requirement based approach. The paper describes the specific models features, the architectures of the implemented software systems and its validation process. Performed validation tests highlighted the capability of the simulation environment to guarantee in real-time the required functionalities and performance of the simulated avionics systems, as well as to reproduce the interaction between these systems, thus permitting a realistic and reliable simulation of a complete mission scenario.
Location Detection of Vehicular Accident Using Global Navigation Satellite Systems/Inertial Measurement Units Navigator
Vehicle tracking and accident recognizing are considered by many industries like insurance and vehicle rental companies. The main goal of this paper is to detect the location of a car accident by combining different methods. The methods, which are considered in this paper, are Global Navigation Satellite Systems/Inertial Measurement Units (GNSS/IMU)-based navigation and vehicle accident detection algorithms. They are expressed by a set of raw measurements, which are obtained from a designed integrator black box using GNSS and inertial sensors. Another concern of this paper is the definition of accident detection algorithm based on its jerk to identify the position of that accident. In fact, the results convinced us that, even in GNSS blockage areas, the position of the accident could be detected by GNSS/INS integration with 50% improvement compared to GNSS stand alone.
Virtual 3D Environments for Image-Based Navigation Algorithms
This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.
Innovative Design Considerations for Adaptive Spacecraft
Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.
, low earth orbit
, medium earth orbit
, geostationary earth orbit
, self-organizing control system
, anti-satellite weapons
, orbital control
, radar warning receiver
, missile warning receiver
, laser warning receiver
, attitude and orbit control systems
, command and data handling.
Health Monitoring and Failure Detection of Electronic and Structural Components in Small Unmanned Aerial Vehicles
Fully autonomous small Unmanned Aerial Vehicles
(UAVs) are increasingly being used in many commercial applications.
Although a lot of research has been done to develop safe, reliable
and durable UAVs, accidents due to electronic and structural failures
are not uncommon and pose a huge safety risk to the UAV operators
and the public. Hence there is a strong need for an automated health
monitoring system for UAVs with a view to minimizing mission
failures thereby increasing safety. This paper describes our approach
to monitoring the electronic and structural components in a small
UAV without the need for additional sensors to do the monitoring.
Our system monitors data from four sources; sensors, navigation
algorithms, control inputs from the operator and flight controller
outputs. It then does statistical analysis on the data and applies
a rule based engine to detect failures. This information can then
be fed back into the UAV and a decision to continue or abort the
mission can be taken automatically by the UAV and independent of
the operator. Our system has been verified using data obtained from
real flights over the past year from UAVs of various sizes that have
been designed and deployed by us for various applications.
Robot Navigation and Localization Based on the Rat’s Brain Signals
The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.
Visual Search Based Indoor Localization in Low Light via RGB-D Camera
Most of traditional visual indoor navigation algorithms
and methods only consider the localization in ordinary daytime, while
we focus on the indoor re-localization in low light in the paper. As
RGB images are degraded in low light, less discriminative infrared
and depth image pairs are taken, as the input, by RGB-D cameras, the
most similar candidates, as the output, are searched from databases
which is built in the bag-of-word framework. Epipolar constraints can
be used to relocalize the query infrared and depth image sequence.
We evaluate our method in two datasets captured by Kinect2. The
results demonstrate very promising re-localization results for indoor
navigation system in low light environments.
Fuzzy Inference System for Determining Collision Risk of Ship in Madura Strait Using Automatic Identification System
Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.
Augmenting Navigational Aids: The Development of an Assistive Maritime Navigation Application
On the bridge of a ship the officers are looking for visual aids to guide navigation in order to reconcile the outside world with the position communicated by the digital navigation system. Aids to navigation include: Lighthouses, lightships, sector lights, beacons, buoys, and others. They are designed to help navigators calculate their position, establish their course or avoid dangers. In poor visibility and dense traffic areas, it can be very difficult to identify these critical aids to guide navigation. The paper presents the usage of Augmented Reality (AR) as a means to present digital information about these aids to support navigation. To date, nautical navigation related mobile AR applications have been limited to the leisure industry. If proved viable, this prototype can facilitate the creation of other similar applications that could help commercial officers with navigation. While adopting a user centered design approach, the team has developed the prototype based on insights from initial research carried on board of several ships. The prototype, built on Nexus 9 tablet and Wikitude, features a head-up display of the navigational aids (lights) in the area, presented in AR and a bird’s eye view mode presented on a simplified map. The application employs the aids to navigation data managed by Hydrographic Offices and the tablet’s sensors: GPS, gyroscope, accelerometer, compass and camera. Sea trials on board of a Navy and a commercial ship revealed the end-users’ interest in using the application and further possibility of other data to be presented in AR. The application calculates the GPS position of the ship, the bearing and distance to the navigational aids; all within a high level of accuracy. However, during testing several issues were highlighted which need to be resolved as the prototype is developed further. The prototype stretched the capabilities of Wikitude, loading over 500 objects during tests in a major port. This overloaded the display and required over 45 seconds to load the data. Therefore, extra filters for the navigational aids are being considered in order to declutter the screen. At night, the camera is not powerful enough to distinguish all the lights in the area. Also, magnetic interference with the bridge of the ship generated a continuous compass error of the AR display that varied between 5 and 12 degrees. The deviation of the compass was consistent over the whole testing durations so the team is now looking at the possibility of allowing users to manually calibrate the compass. It is expected that for the usage of AR in professional maritime contexts, further development of existing AR tools and hardware is needed. Designers will also need to implement a user-centered design approach in order to create better interfaces and display technologies for enhanced solutions to aid navigation.
The Role of Planning and Memory in the Navigational Ability
Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory.
Exploring Pisa Monuments Using Mobile Augmented Reality
Augmented Reality (AR) has taken a big leap with the introduction of mobile applications which co-locate bi-dimensional (e.g. photo, video, text) and tridimensional information with the location of the user enriching his/her experience. This study presents the advantages of using Mobile Augmented Reality (MAR) technologies in traveling applications, improving cultural heritage exploration. We propose a location-based AR application which combines co-location with the augmented visual information about Pisa monuments to establish a friendly navigation in this historic city. AR was used to render contextual visual information in the outdoor environment. The developed Android-based application offers two different options: it provides the ability to identify the monuments positioned close to the user’s position and it offers location information for getting near the key touristic objectives. We present the process of creating the monuments’ 3D map database and the navigation algorithm.
A Route Guidance System for Car Finding in Indoor Parking Garages
This paper presents a route guidance system for car owners to find their cars in parking garages. The presents system comprises a positioning-assisting subsystem and a car-finding mobile app. The positioning-assisting subsystem mainly uses the iBeacon technology for indoor positioning. The car-finding mobile app guides car owners to their cars based on a non-map navigation strategy. This study also designs a virtual coordinate system to support identifying the locations of parking spaces and iBeacon devices. We use Arduino and Android as the platforms to implement the proposed positioning-assisting subsystem and car-finding mobile app, respectively. We have also deployed the system in a parking garage in our campus for testing. Experimental results verify that our system can efficiently and correctly guide car owners to the parking spaces of their cars.
An Indoor Guidance System Combining Near Field Communication and Bluetooth Low Energy Beacon Technologies
Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study presents a methodology based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoor and outdoor on smartphones, with aim to provide users a smart life through this system. The presented system is implemented on a smartphone and evaluated on a student campus environment. The experimental results confirm the ability of the presented app to switch automatically from an outdoor mode to an indoor mode and to guide the user to the requested target destination via the shortest possible route.
Studies on Affecting Factors of Wheel Slip and Odometry Error on Real-Time of Wheeled Mobile Robots: A Review
In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.
Information Requirements for Vessel Traffic Service Operations
Operators of vessel traffic service (VTS) center provides three different types of services; namely information service, navigational assistance and traffic organization to vessels. To provide these services, operators monitor vessel traffic through computer interface and provide navigational advice based on the information integrated from multiple sources, including automatic identification system (AIS), radar system, and closed circuit television (CCTV) system. Therefore, this information is crucial in VTS operation. However, what information the VTS operator actually need to efficiently and properly offer services is unclear. The aim of this study is to investigate into information requirements for VTS operation. To achieve this aim, field observation was carried out to elicit the information requirements for VTS operation. The study revealed that the most frequent and important tasks were handling arrival vessel report, potential conflict control and abeam vessel report. Current location and vessel name were used in all tasks. Hazard cargo information was particularly required when operators handle arrival vessel report. The speed, the course, and the distance of two or several vessels were only used in potential conflict control. The information requirements identified in this study can be utilized in designing a human-computer interface that takes into consideration what and when information should be displayed, and might be further used to build the foundation of a decision support system for VTS.
Foundation of the Information Model for Connected-Cars
Recent progress in the next generation of automobile
technology is geared towards incorporating information technology
into cars. Collectively called smart cars are bringing intelligence to
cars that provides comfort, convenience and safety. A branch of smart
cars is connected-car system. The key concept in connected-cars is the
sharing of driving information among cars through decentralized
manner enabling collective intelligence. This paper proposes a
foundation of the information model that is necessary to define the
driving information for smart-cars. Road conditions are modeled
through a unique data structure that unambiguously represent the time
variant traffics in the streets. Additionally, the modeled data structure
is exemplified in a navigational scenario and usage using UML.
Optimal driving route searching is also discussed using the proposed
data structure in a dynamically changing road conditions.
Comparison of Different k-NN Models for Speed Prediction in an Urban Traffic Network
A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.
Questions Categorization in E-Learning Environment Using Data Mining Technique
Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Winged Test Rocket with Fully Autonomous Guidance and Control for Realizing Reusable Suborbital Vehicle
This paper presents the strategic development plan of
winged rockets WIRES (WInged REusable Sounding rocket) aiming
at unmanned suborbital winged rocket for demonstrating future fully
reusable space transportation technologies, such as aerodynamics,
Navigation, Guidance and Control (NGC), composite structure,
propulsion system, and cryogenic tanks etc., by universities in
collaboration with government and industries, as well as the past and
current flight test results.
Super-ellipsoidal Potential Function for Autonomous Collision Avoidance of a Teleoperated UAV
In this paper, we present the design of the
super-ellipsoidal potential function (SEPF), that can be used for
autonomous collision avoidance of an unmanned aerial vehicle (UAV)
in a 3-dimensional space. In the design of SEPF, we have the
full control over the shape and size of the potential function. In
particular, we can adjust the length, width, height, and the amount
of flattening at the tips of the potential function so that the collision
avoidance motion vector generated from the potential function can
be adjusted accordingly. Based on the idea of the SEPF, we also
propose an approach for the local autonomy of a UAV for its collision
avoidance when the UAV is teleoperated by a human operator. In
our proposed approach, a teleoperated UAV can not only avoid
collision autonomously with other surrounding objects but also track
the operator’s control input as closely as possible. As a result, an
operator can always be in control of the UAV for his/her high-level
guidance and navigation task without worrying too much about
the UAVs collision avoidance while it is being teleoperated. The
effectiveness of the proposed approach is demonstrated through a
human-in-the-loop simulation of quadrotor UAV teleoperation using
virtual robot experimentation platform (v-rep) and Matlab programs.
Tactile Sensory Digit Feedback for Cochlear Implant Electrode Insertion
Cochlear Implantation (CI) which became a routine
procedure for the last decades is an electronic device that provides a
sense of sound for patients who are severely and profoundly deaf.
The optimal success of this implantation depends on the electrode
technology and deep insertion techniques. However, this manual
insertion procedure may cause mechanical trauma which can lead to
severe destruction of the delicate intracochlear structure.
Accordingly, future improvement of the cochlear electrode implant
insertion needs reduction of the excessive force application during
the cochlear implantation which causes tissue damage and trauma.
This study is examined tool-tissue interaction of large prototype scale
digit embedded with distributive tactile sensor based upon cochlear
electrode and large prototype scale cochlea phantom for simulating
the human cochlear which could lead to small scale digit
requirements. The digit, distributive tactile sensors embedded with
silicon-substrate was inserted into the cochlea phantom to measure
any digit/phantom interaction and position of the digit in order to
minimize tissue and trauma damage during the electrode cochlear
insertion. The digit have provided tactile information from the digitphantom
insertion interaction such as contact status, tip penetration,
obstacles, relative shape and location, contact orientation and
multiple contacts. The tests demonstrated that even devices of such a
relative simple design with low cost have potential to improve
cochlear implant surgery and other lumen mapping applications by
providing tactile sensory feedback information and thus controlling
the insertion through sensing and control of the tip of the implant
during the insertion. In that approach, the surgeon could minimize the
tissue damage and potential damage to the delicate structures within
the cochlear caused by current manual electrode insertion of the
cochlear implantation. This approach also can be applied to other
minimally invasive surgery applications as well as diagnosis and path
Mobile App versus Website: A Comparative Eye-Tracking Case Study of Topshop
The UK is leading in online retail and mobile
adoption. However, there is a dearth of information relating to mobile
apparel retail, and developing an understanding about consumer
browsing and purchase behaviour in m-retail channel would provide
apparel marketers, mobile website and app developers with the
necessary understanding of consumers’ needs. Despite the rapid
growth of mobile retail businesses, no published study has examined
shopping behaviour on fashion mobile apps and websites. A mixed method approach helped to understand why fashion
consumers prefer websites on smartphones, when diverse mobile
apps are also available. The following research methods were
employed: survey, eye-tracking experiments, observation, and
interview with retrospective think aloud. The mobile gaze tracking
device by SensoMotoric Instruments was used to understand
frustrations in navigation and other issues facing consumers in
mobile channel. This method helped to validate and compliment
other traditional user-testing approaches in order to optimize user
experience and enhance the development of mobile retail channel.
The study involved eight participants - females aged 18 to 35 years
old, who are existing mobile shoppers. The participants used the
Topshop mobile app and website on a smart phone to complete a task
according to a specified scenario leading to a purchase. The
comparative study was based on: duration and time spent at different
stages of the shopping journey, number of steps involved and product
pages visited, search approaches used, layout and visual clues, as
well as consumer perceptions and expectations. The results from the data analysis show significant differences in
consumer behaviour when using a mobile app or website on a smart
phone. Moreover, two types of problems were identified, namely
technical issues and human errors. Having a mobile app does not
guarantee success in satisfying mobile fashion consumers. The
differences in the layout and visual clues seem to influence the
overall shopping experience on a smart phone. The layout of search
results on the website was different from the mobile app. Therefore,
participants, in most cases, behaved differently on different
platforms. The number of product pages visited on the mobile app
was triple the number visited on the website due to a limited visibility
of products in the search results. Although, the data on traffic trends
held by retailers to date, including retail sector breakdowns for visits
and views, data on device splits and duration, might seem a valuable
source of information, it cannot explain why consumers visit many
product pages, stay longer on the website or mobile app, or abandon
the basket. A comprehensive list of pros and cons was developed by
highlighting issues for website and mobile app, and recommendations
provided. The findings suggest that fashion retailers need to be aware of
actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added
to which is the challenge of retaining existing and acquiring new
customers. There seem to be differences in the way fashion
consumers search and shop on mobile, which need to be explored in
A Low-Cost Vision-Based Unmanned Aerial System for Extremely Low-Light GPS-Denied Navigation and Thermal Imaging
This paper presents the design and implementation
details of a complete unmanned aerial system (UAS) based
on commercial-off-the-shelf (COTS) components, focusing on
safety, security, search and rescue scenarios in GPS-denied
environments. In particular, The aerial platform is capable
of semi-autonomously navigating through extremely low-light,
GPS-denied indoor environments based on onboard sensors only,
including a downward-facing optical flow camera. Besides, an
additional low-cost payload camera system is developed to stream
both infra-red video and visible light video to a ground station in
real-time, for the purpose of detecting sign of life and hidden humans.
The total cost of the complete system is estimated to be $1150,
and the effectiveness of the system has been tested and validated
in practical scenarios.